Demand Planning: The Future of Demand Side Management

Electric utilities have a process by which they project future expected
demand for electricity, and then find resources, either new electric generation
or energy efficiency (Demand Side Management, or DSM) resources to meet that
expected demand, or reduce that demand. Progressive utilities and utility
regulators now include DSM among the mix of resources as a matter of
course. According to Martin Kushler, of the American
Council for an Energy Efficient Economy (ACEEE) who spoke at the Southwest
Regional Energy Efficiency Workshop about an upcoming report from ACEEE, DSM
resources cost an average of 3 cents per kWh of energy saved, much lower than
the typical 10 cents per kWh for new supply side resources. Since saving
energy is not only considerably cheaper but also cleaner than new generation,
including renewables, DSM resources deserve pride of place in resource planning.

Bringing DSM into resource planning has required that utility regulators
change utility incentives to assure that utilities will not be undermining their
own profits. In many states, this has been a slow revolution moving from
traditional "least cost" planning, which focused on achieving the
lowest possible cost per unit of electricity delivered, to a focus on reducing
overall energy bills (either by reducing kWh used, or minimizing the price per
kWh.) This goes against traditional utility instincts, which like most businesses
would like to expand by increasing sales, but can be achieved by paying for
reliable service, or giving incentives for efficiency.

However, there has always been one aspect of DSM which utilities have little
problem with, which are various measures to reduce peak loads, either through
Demand Response (payments to customers in return for turning off equipment
during peak times) and peak shaving (efficiency measures which reduce peak load
by shifting loads to other times of the day.) Reducing peak load is in the
utility's interest because it improves system reliability without significantly
reducing total sales or expensive expenditures on peaking plants which are only
used for a tiny fraction of the year.

Utility-Think

The traditional thinking breaks down demand into a base load piece,
which is basically the least amount used at any time during the year, and any
demand above that level. Traditionally, utilities sought to meet this
demand with a mixture of base load (which runs nearly all the time) and
dispatchable generation (which can be controlled, and is brought on as
necessary). This thinking has run
into problems as intermittent generation, such as wind and solar.

Typically, utilities express these problems as problems with intermittent
technologies, calling them "unreliable," which they are if you
define "reliable" as only those resources which are on 90% of the
time, or which can be called on at will. That is not the definition of
reliability most of us use: most people would call something reliable if it's
there when you expect it to be. With the colloquial definition, the rising
and setting of the sun is about as reliable as anything gets, and the
reliability of solar and wind power also follow predictable daily and seasonal
cycles, limited only by our ability to predict cloudiness and
windiness.

Admittedly, weather prediction is not the most reliable of sciences,
especially when attempting to predict weather in small areas or gusts of wind or
shadows from clouds in small areas. However, geographic diversification
can smooth the fluctuations in generation from gusts of wind or shadows of
clouds in an electric system with multiple solar or wind facilities spread over
a broader area. The remaining unpredictability of generation for such a
diversified system should be manageable by a system which has no trouble coping
with customers' unpredictable and wildly fluctuating demands for electricity.

A typical
"reliable" combined-cycle gas turbine [pdf], takes 3 hours to
start from cold, and can ramp up or down only 7% in power output per
minute. On this time scale weathermen tend to be fairly accurate over
broad regions and a few hours ahead; weathermen earn their reputation for
unreliability due to the surprises which arise in forecasts for a day or two
ahead, and even here improvements
are on the way. For minutes ahead, the wind speed around the field
should give operators a good idea of the strength of wind approaching it.

Implications for DSM

The same narrow focus on dispatchable and base load generation also leads to
a focus on only two types of demand management in electric utility DSM
programs. These programs are almost universally evaluated on (and hence
focus on achieving) three things:

Overall energy reduction (kWh savings)

Peak load reduction (usage at peak times)

Demand response (load reduction which can be called upon in times of
need.)

As I argued in my article on Wind
Power and Heat Pumps, there are other valuable aspects of managing demand
than just these three factors. While electricity is most expensive to
generate at times of peak use, the costs vary greatly throughout the
rest of the year as well. In addition to the load on the system, the cost
of natural gas is considerably higher in the winter than the summer, meaning
that saving the same kWh of energy at the same level of load is worth more in
the winter than in the summer, so long as the kWh would have been generated
using the same amount of natural gas at the two times.

To be fair, the cost/benefit tests used to evaluate the effectiveness of DSM
measures often do take into account such cost factors as the fuel cost I
point to above, but in my experience, it is a very imprecise process, with very
little attention given to timing of the savings ("load shape") beyond
an attempt to quantify the coincidence with peak. At a discussion with
Xcel Energy (NYSE:XEL) where they were soliciting feedback from stakeholders for
the goals of a DSM Potential Study, they did not intend to ask the contractor
for load shape information of various measures evaluated until I raised the
issue.

Demand Planning

Over the longer term, as more electricity is generated by intermittent
sources, load shape information will become increasingly important. Rather
than a focus on reducing peak load, the focus will need to shift to reducing
load when it exceeds available intermittent resources, and increasing useful use
of electricity when renewable energy is most abundant. At even relatively
small penetrations, solar
generation can exceed demand on sunny mornings when the temperature is
moderate, while wind
can exceed demand on windy nights, especially in the winter. Even
before we add enough renewables to the system that they begin to exceed demand
at these times, we need to be thinking about shifting future demand to those
times of relative plenty, and from those times of relative scarcity.

Such shift can easily be accomplished with electricity storage, but such
storage can be quite expensive. A more economic option would be
encouraging customer choices today which influence the patterns of future
load. Even if we can't predict how windy it will be a week from now, we
know, climate change notwithstanding, the daily and annual patterns of sun and
wind five, ten, and twenty years from now. We also can reasonably expect
that both wind and solar electric generation will be much higher than it is
today. That extra generation will be added as part of the utilities normal
process of Resource Planning, in which DSM is now finding its place. The
next logical step is Demand Planning, using utility DSM programs and other tools
to better meet the available future electric resource with future electric
demand, supplying useful electric services to make our lives better.

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Comments

"Such shift can easily be accomplished with electricity storage, but such storage can be quite expensive. A more economic option would be encouraging customer choices today which influence the patterns of future load."

By encouraging customer choices, I can only assume that you mean offering different prices based on the time of peak demand, but doing so would ultimately make the case for distributed energy storage along the lines of what Gridpoint and similar companies seem to be doing. Because if a consumer can buy energy at off-peak prices and store it locally, they (or the utility) will recoup the investment in the storage much faster. Don't you think?

Time of day pricing cis part of this. Just having time of day pricing is not necessarily enough to gaurantee that storage will be economic, and it is only one of many measures that a consumer can use to ship his or her load. Simply choosing to run the diswasher or dryer off peak is another. To bring this back to demand planning, the utility could encourage the save of appliances with a timed delay feature, which would make it easier for customers to shift their load off peak.